Data Science is a study to extract information from data.

Data Science is a new term of science which belongs to Data. Data Science is a study to solve the real world problem on the basis of enormous amount of data. Data is a source of information and problem solution. Data Science is the hottest Job in the World. World is surrounded by data, it is everywhere now days. A study shows that an amount of data has doubled in last 10 years comparing to all previous years. Data has increased in millions of Terra Bytes in the world. Biggest source of data is Social Media Platforms, Mobile Devices, Web Data, Business Data, Historical Data and many more. Companies want to use this large amount of data to solve their business problems like Customer Engagement, Sales Increment, Research, Automation etc.

Data Science is everywhere now but What is Data Science? Here is the Data Science Definition, “Data Science is a study to extract useful information from the data which solves the real world problem”. It is the way to get insights of data with the help of Machine Learning. Companies like Netflix, Facebook, Amazon, and Apple etc. are using data science to get the key information of users like interest, hobbies, choice, styles, needs and many more. These insights of data are very useful for big giants companies to update their products and services. They clearly understand that what customer wants to see, wants to buy, wants to listen, where to travel, what are their financial needs and many more. Now companies suggest and recommend to customer according to their past history data like movie recommendation, product suggestion, music recommendation, ads presentation, shortest path suggestion etc.

Data Science Processing Cycle

Data Science has a complete process cycle to get useful information from an enormous amount of data which solves the biggest real world problem.
It has various stages of different operations to solve the problem.
1. Define Business Problem
2. Data Gathering (Collection of data)
3. Data Filtering (Cleaning of data)
4. Data Analysis (Selection of Algorithm)
5. Data Modeling (Build a Model)
6. Visualization (Output Presentation)
7. Deployment (Deploy the Model)

If a company wants to solve any problem with the help of data science then it has to perform on all stages of complete process.
A Data Scientist or Engineer has to understand the problem first with lots of queries in a detail manner. A good Data Scientist always asks many questions from the client regarding problem. Secondly collect the data from various sources like web, mobile, historical data etc. Thirdly clean the data and remove all unwanted stuff and errors from the data. Fourthly analyze the data and select the best machine learning algorithm to solve the problem. After that build the model on the basis of training input data. Test the trained model with new data set and visualize the output result in the form of graphs, charts etc.
Lastly if output is satisfied then deploy the model and use it in real world to solve the problem. Keep updating the model to maintain it.

Data Science solves so many real problem of world. Many companies like Facebook, Amazon, Microsoft, Netflix, Uber etc. are using this technology to solve their problems and updates their product and services. Netflix Movies Recommendation, Spotify Music Recommendation, Amazon Product Suggestion, Google Ads Presentation are some real data science solution for the world. Many Online and Offline Data Science Courses are running in India and all over the world. Lots of Data Science stuff including Data Science Syllabus and Notes are available online on many platforms. If you are a computer science student then you can also join any Data Science Internship in any company to get good practical experience. Data Science Salary is really high and will get good boost up in career.

Data Science Sectors:
Social Media
Smart Devices

Data Science Jobs:
Data Scientist
Data Engineer
Data Architect
Data Analyst
Business Analyst
Big Data Analytic
Data Administration

Data Science Skills:
Database (My Sql, No Sql, Oracle)
Maths (Statistics, Probability)
Programming (Python, R, Sas)
Data Operations (Cleaning and Organizing)
Machine Learning (Classification, Regression)
Big Data (Hadoop, Spark)
Data Visualization (Tableau, Power BI)

Data Scientist Interviews
Abhishek Thakur Interview
Krish Naik Interview